Knowledge Growth and the Allocation of Time

By Robert E. Lucas, Benjamin Moll. Journal of Political Economy, 2014

432 citations recorded by the source corpus.

We analyze a model economy with many agents, each with a different productivity level. Agents divide their time between two activities: producing goods with the production-related knowledge they already have and interacting with others in search of new, productivity-increasing ideas. These choices jointly determine the economy’s current production level and its rate of learning and real growth. We construct the balanced growth path for this economy. We also study the allocation chosen by an idealized planner who takes into account and internalizes the external benefits of search. Finally, we provide three examples of alternative learning technologies and show that the properties of equilibrium allocations are quite sensitive to two of these variations.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/74f82bc290c5d379501183bdb5b8904f5f1537ad

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Citations in the corpus

The Dynamics of Inequality (2016, neutral): “However, non-linear differential operators can arise in models of knowledge diffusion (e.g. Perla and Tonetti, 2014; Lucas and Moll, 2014; Benhabib, Perla, and Tonetti, 2016).”
Life Cycle Wage Growth across Countries (2017, methodology): “For example, the models of Lucas (2009), Lucas and Moll (2014), and Perla and Tonetti (2014) posit that human capital is accumulated through social interactions with others; all determinants of the frequency or quality of such interactions are potential determinants of cross-country differences in…”
Mean Field Games Models—A Brief Survey (2013, background): “Various applications and additional models have been worked out in detail in [7, 10, 41, 53, 54, 67, 75, 79, 81, 84, 86, 87] (see also the special edition on Netw.”
Catch-up and fall-back through innovation and imitation (2013, neutral): “Perla and Tonetti (2013) and Lucas and Moll (2013) use random search models to focus on the feedback relationship between the entire endogenously determined productivity distribution and optimal technology adoption decisions.”
The Rise of American Ingenuity: Innovation and Inventors of the Golden Age (2017, neutral): “These types of data are crucial to understanding the relationship between human capital and economic growth (e.g., Lucas (2009), Alvarez et al. (2013), Lucas and Moll (2014), Perla and Tonetti (2014)).”
Endogenous Production Networks (2020, neutral): “Finally, it is also not due to thick-tailed productivity draws that continuously improve technology and spreading in the economy via a diffusion process (as in Akcigit, Celik, and Greenwood (2016), Lucas (2009), Lucas and Moll (2014), or Perla and Tonetti (2014)).”
Existence and Uniqueness of Solutions for Bertrand and Cournot Mean Field Games (2015, background): “[22] R. E. Lucas Jr and B. Moll, Knowledge growth and the allocation of time, tech. report, National Bureau of Economic Research, 2011.”